Jonathan Chapman, M. Dean, Pietro Ortoleva, E. Snowberg, Colin Camerer
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引用次数: 25

摘要

我们研究了大量行为规律之间的关联模式,目的是为更全面的决策理论创造经验基础。通过对美国人口的代表性样本(n= 1000)进行激励调查,我们引出了21种行为。我们的数据显示,这些指标之间的相关性有一个清晰而相对简单的结构。使用主成分分析,我们将21个变量减少到6个组件,对应于明确的高相关性集群。我们研究了这些组成部分、认知能力和人口统计学之间的关系。常见的现存理论与我们数据中的所有模式并不兼容。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Econographics
We study the pattern of correlations across a large number of behavioral regularities, with the goal of creating an empirical basis for more comprehensive theories of decision-making. We elicit 21 behaviors, using an incentivized survey on a representative sample (n=1,000) of the US population. Our data show a clear and relatively simple structure underlying the correlations between these measures. Using principal components analysis, we reduce the 21 variables to six components corresponding to clear clusters of high correlations. We examine the relationship between these components, cognitive ability, and demographics. Common extant theories are not compatible with all the patterns in our data.
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